Direct Inference (Static Calculation). Pretrained CHGNet can predict the energy (eV/atom), force (eV/A), stress (GPa) and magmom ( μ B ) of a given structure. Tuning CHGNet · CHGNet Basics · Discussions · Issues

The parsed python dictionary includes information for CHGNet inputs (structures), and CHGNet prediction labels (energy, force, stress ,magmom).

This notebook shows example to load the CHGNet for prediction. In [ ]: try: from chgnet.model import CHGNet except ImportError: # install CHGNet (only needed ...

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov - chgnet/chgnet/model/model.py at main ...

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov - chgnet/chgnet/model/dynamics.py at main ...

17 сент. 2024 г. · 0.3.0 version: Improved pretrained weights released. We release the most recent pretrained model: CHGNet 0.3.0 (see details)

This notebook shows how to visualize a CHGNet relaxation trajectory in a Plotly Dash app using Crystal Toolkit. Running the last cell in this notebook should ...

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov - chgnet/chgnet/utils/vasp_utils.py at main ...

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CHGNet highlights its ability to study electron interactions and charge distribution in atomistic modeling with near DFT accuracy.